We propose an extension of recursive cascade correlation (RCC) for structured domains which is able to partially remove the causality assumption. In fact, the proposed model, i.e. contextual recursive cascade correlation, is able to exploit contextual information stored in frozen units. Experimental results, obtained on the prediction of the boiling point of alkanes, show the superiority of the proposed approach versus RC
This article extends the combinatorial approach to support the determination of contextuality amidst...
We present the application of Cascade Correlation for structures to QSPR (quantitative structure-pro...
This thesis is concerned with modelling contextuality in the fields of Quantum Information Science a...
We propose an extension of recursive cascade correlation (RCC) for structured domains which is able ...
We propose an extension of Recursive Cascade Correlation (RCC) for structured domains which is able ...
This paper propose a first approach to deal with contextual information in structured domains by rec...
In this section, the capacity of statistical machine learning techniques for recursive structure pro...
In this note we consider the Contextual Recursive Cascade Correlation model (CRCC), which is able to...
In this note we consider the Contextual Recursive Cascade Correlation model (CRCC), which is able t...
Recurrent neural networks fail to deal with prediction tasks, which do not satisfy the causality ass...
Recurrent neural networks fail to deal with prediction tasks which do not satisfy the causality assu...
Cascade correlation (CC) constitutes a training method for neural networks that determines the weigh...
Recurrent Cascade-Correlation (RCC) is a recurrent version of the Cascade-Correlation learning archi...
We propose a Relational Neural Network defined as a special instance of the Recurrent Cascade Correl...
A method is given which uses subject matter assumptions to discriminate recursive models and thus po...
This article extends the combinatorial approach to support the determination of contextuality amidst...
We present the application of Cascade Correlation for structures to QSPR (quantitative structure-pro...
This thesis is concerned with modelling contextuality in the fields of Quantum Information Science a...
We propose an extension of recursive cascade correlation (RCC) for structured domains which is able ...
We propose an extension of Recursive Cascade Correlation (RCC) for structured domains which is able ...
This paper propose a first approach to deal with contextual information in structured domains by rec...
In this section, the capacity of statistical machine learning techniques for recursive structure pro...
In this note we consider the Contextual Recursive Cascade Correlation model (CRCC), which is able to...
In this note we consider the Contextual Recursive Cascade Correlation model (CRCC), which is able t...
Recurrent neural networks fail to deal with prediction tasks, which do not satisfy the causality ass...
Recurrent neural networks fail to deal with prediction tasks which do not satisfy the causality assu...
Cascade correlation (CC) constitutes a training method for neural networks that determines the weigh...
Recurrent Cascade-Correlation (RCC) is a recurrent version of the Cascade-Correlation learning archi...
We propose a Relational Neural Network defined as a special instance of the Recurrent Cascade Correl...
A method is given which uses subject matter assumptions to discriminate recursive models and thus po...
This article extends the combinatorial approach to support the determination of contextuality amidst...
We present the application of Cascade Correlation for structures to QSPR (quantitative structure-pro...
This thesis is concerned with modelling contextuality in the fields of Quantum Information Science a...